Expert System Method Research Articles

Cooperative enhanced scatter search with opposition-based learning schemes for parameter estimation in high dimensional kinetic models of biological systems

Industrial bioprocesses development nowadays is concerned with producing chemicals using yeast, bacteria and therapeutic proteins in mammalian cells. This involves the utilization of microorganism cells as factories and re-engineering them in silico. The tools that could facilitate this process are known as the kinetic models. Kinetic models of cellular metabolism are important in assisting researchers to understand the rational design of biological systems, predicting metabolites production, and improving bio-products development. However, the most challenging task in model development is parameter estimation, which is the process of identifying an unknown value of model parameters which provides the best fit between the model output and a set of experimental data. Due to the increased complexity and high dimensionality of the models, which are extremely nonlinear and contain large numbers of kinetic parameters, parameter estimation is known to be difficult and time-consuming. This study proposes a cooperative enhanced scatter search with opposition-based learning schemes (CeSSOL) for parameter estimation in large-scale biology models. The method was executed in parallel with the proposed cooperative mechanism in order to exchange information (kinetic parameters) between individual threads. Each thread consists of different parameters settings that enhance the systemic properties in obtaining the global minimum. The performance of the proposed method was assessed against two large-scale microorganisms models using mammalian and bacteria cells. The results revealed that the proposed method recorded faster computation time compared to other methods. The study has also demonstrated that the proposed method can be used to provide more accurate and faster estimation of kinetic models, indicating the potential benefits of utilizing this method for expert systems of industrial biotechnology.

Perancangan Sistem Pakar Untuk Mendiagnosa Penyakit Diabetes Mellitus Menggunakan Metode Certainty Factor Design Expert System for Diagnosing Diabetes Mellitus Using Certainty Factor Method

Diabetes mellitus is a chronic metabolic disorder caused by the pancreas that does not produce enough insulin, so the body works to be disturbed. But by knowing the symptoms that exist, prevention of diabetes mellitus disease can be done as early as possible with the help of expert systems.One method of expert system used to diagnose symptoms of Diabetes Mellitus is Certainty Factor. The process undertaken in this research starts from literature studies, system design, system implementation and the last is testing the system. In the system design process is done by designing the database required by the expert system and also design the system interface design. After the design process is done then the next step is to implement the design into an expert system application. By using this method, the system gives results of possible symptoms experienced, presentation of beliefs, and treatment solutions based on the facts and the value of confidence given by users in filling out questions that have been given by the system.The results of this system are used to help medical personnel and patients in order to identify the symptoms of diabetes mellitus

An Expert System for Pneumococcal Prognosis

Threats and viruses are particularly alarming for children with low immunization levels. Pneumococcal disease is the world's most important cause of child death and has claimed many lives. Since awareness of the dangers of Pneumococcal viruses among parents is low in Malaysia, preventive measures such as vaccine intake cannot be done comprehensively. Hence, in order to communicate information about Pneumococcal disease, a pneumococcal disease diagnosis system for children is developed. This system employs expert system method and apply forward chaining technique for its reasoning. Knowledge base of the system is stored in the database for data management. This alternative system allows access to information as well as early diagnosis of early symptoms can be detected. This system is expected to benefit users in terms of knowledge sharing, and self-checking on their body condition, especially parents, to prevent any possible diseases that may infect children's.

Analisa Dan Perbandingan Sistem Aplikasi Diagnosa Penyakit Asma Dengan Algoritma Certainty Factor Dan Algoritma Decision Tree Berbasis Android

A computer is a tool that become the needs of society, both in the society in general, educational institutions, industry and even in the world of health, in the issue of health scope using technology, there are several cases that can be implemented, one of which is knowledge. Knowledge is a science that a person has acquired where the knowledge takes a long time to get it, sometimes someone with knowledge needs to store that knowledge, there are many methods in storing knowledge, from noting to books, videos and even giving it to someone else, but the method takes a long time, the expert system can be one solution in the knowledge where the expert system is a system that can be incorporated knowledge and store knowledge in the system, there are many expert system methods such as expert system method using Certainty Factor algorithm and algorithm Decision Tree. In the problem taken is to analyze, where asthma disease is the five largest disease that causes death in the world that varies between 6-30% (around 16.5%). In making the system using the waterfall model procedure and the program created using web display for admin management and display android device for user interface, the purpose of which is done in this research is with the application of expert systems & artificial intelligence, users or community will be knowing way and first handling in overcoming the asthma disease where the implementation of applications based on android smartphone, which can be used anywhere.

Computerized and distance learning systems (the case of medical diagnostics)

The purpose of this paper is to analyze the current state and the possibility of developing computer systems of various types in education (the case of medicine). Particular emphasis is on the use of case studies that combine linguistic and multimedia components and on intellectual technologies to implement the learning process, individually controlled at different stages. The considered methods of knowledge engineering in the construction of intelligent systems form the skills of individual and teamwork. A separate aspect is the methods and means of distance learning with the use of telemedical and internet technologies in teaching and continuous professional development. Ontologies are used as a means of cognitive visual representation of knowledge. They find application in the presentation of medical knowledge that characterize pathological processes. Intellectual maps and concept maps are used as the primary analysis of logical relationships of characteristics. Role games contribute to the development of knowledge extraction for expert systems. This allows all members of the group to simulate the roles of a knowledge engineer and an expert. In addition, the teacher corrects, if necessary, this process and indicates in conclusion on the mistakes made and the unused possibilities for optimizing the dialogue between the student-cognitive scientist and the student-expert. Based on case-method it is proposed to implement examples and questions from clinical practice, including video fragments. This allows you to monitor the correctness of the actions of students during inspections and manipulations. The expert system and remote methods of work are used for the analysis of microscopic drugs under the supervision of the teacher. Building an intellectual learning system that includes cases is the basis for acquiring the skills of differential diagnosis in the process of examining a virtual patient. Telemedical technologies, using different video cameras, suggest remote teaching of not only theoretical, but also clinical subjects with examination of patients, including testing of students and video examinations. As a result of the research, the author proposed schemes of computerized and intellectualized technology for teaching medical subjects of various types (morphological, clinical, and cybernetic). This contributes to the increase of knowledge, taking into account the individual abilities of students on personal programs, forms skills to extract and analyze the information received. Videoconferencing allows you to improve your skills remotely at the place of work in the process of contact with lecturers and teachers. Specially developed approaches presuppose remote examination and diagnostics under the supervision of the teacher. In addition, demonstration of patients with various pathologies during telelectures. These approaches offer opportunities for individual mastering of knowledge based on modern methods of electronic education and intellectual technologies. Personalization of the approach to learning allows you to repeat the insufficiently mastered sections of the material. Distance learning methods will allow setting and solving tasks of continuous improvement of professional skill of medical workers on a fundamentally new level. In principle, the use of many of these approaches is possible in other areas of education.

Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases

The development of artificial intelligence technology that has occurred has allowed expert systems to be applied in detecting disease using programming languages. One in terms of providing information about a variety of disease problems that have recently been feared by Indonesian society, namely stroke. Expert system method used is dempster shafer and certainty factor method is used to analyze the comparison of both methods in stroke.Based on the analysis result, it is found that certainty factor is better than demster shafer and more accurate in handling the knowledge representation of stoke disease according to the symptoms of disease obtained from one hospital in medan city, uniqueness of algorithm that exist in both methods.

Compressive strength estimation of concrete containing zeolite and diatomite: An expert system implementation

In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days\' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.

Perancangan Sistem Monitoring Penyelesaian Berkas Pidana Dengan Metode Rule Based Expert Systems dan Teknologi Radio Frequency Identification

The process of criminal cases settlement is based on the regulation of time limit on trial. It is difficult to see the each stage of process because of the number of case files handled. To know the status of settlement, it needs monitoring system of RFID technology built by design to a model of Rule Based Expert Systems. It facilitates the process of data files so it can produce the right, quick and accurate report. The priority of criminal case files is based on the level of completion difficulty while the tracking involves 3 locations: police, public prosecutor and district court. Rule Based Expert System method works following an expert's knowledge in solving a problem. The design that has been made is capable of being implemented and according to the user’s needs. It helps to quickly generate the right information of criminal case settling time process.

Enhancing semantic consistency in anti-fraud rule-based expert systems

In this study, an ontology-driven approach is proposed for semantic conflict detection and classification in rule-based expert systems. It focuses on the critical case of anti-fraud rule repositories for the inspection of Card Not Present (CNP) transactions in e-commerce environments. The main motivation is to examine and curate anti-fraud rule datasets to avoid semantic conflicts that could lead the underpinning expert system to incorrectly perform, e. g., by accepting fraudulent transactions and/or by discarding harmless ones. The proposed approach is based on Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) technologies to develop an anti-fraud rule ontology and reasoning tasks, respectively. The three main contributions of this work are: first, the creation of a conceptual knowledge model for describing anti-fraud rules and their relationships; second, the development of semantic rules as conflict-resolution methods for anti-fraud expert systems; third, experimental facts are gathered to evaluate and validate the proposed model. A real-world use case in the e-commerce (e-Tourism) industry is used to explain the ontological knowledge design and its use. The experiments show that ontological approaches can effectively discover and classify conflicts in rule-based expert systems in the field of anti-fraud applications. The proposal is also applicable to other domains where knowledge rule bases are involved.

Determination Model of Suitable Coastal Transit-Oriented Development Location, Case Study: Paotere, Makassar

Commuter and local society, the users of Paotere local port who took round trip to small islands and other island as well, experienced redundancy of cost, time and travel distance in fulfilling their whole needs at the shore of Makassar. Traveling by using motorized vehicle at the shore of Makassar was taken due to the unavailability of needed goods in the port and its neighborhood within radius 500 meters. This research is aimed at establishing determination model of suitable location for spatial planning of coastal Transit-Oriented Development (TOD) in order to eliminate redundancy of cost, time and travel distance. It applied expert system and spatial analysis method based on geographic information system (GIS). The result showed that the most suitable location for coastal TOD development was in local Port and its neighborhood, it was at some grids, 581-585 and 540-542 within walking radius. Used determination model was determination in which, relied on highest value of the location with supports from its neighborhood location as well and the correlation among; certainty factor, commuter’s activity and local society.

Web based fuzzy diagnosis system and evaluation for five diseases with sort throat symptom

Automatic disease diagnosis has been human concern for a long time. Since people are so busy and the doctors visit expenses areso expensive, a lot of different attempts have been done in the field of design of expert system for disease diagnosis. This paper describes aproject work aiming to develop a web based fuzzy expert system for human disease diagnosis. This program models the thinking pattern andhuman activity and leads to close the expert system and human action method. In this paper we have consulted with different physicians andanalyzed the diagnosis procedure and modeled them with a fuzzy expert system. This project is based on development of a web-based clinicaltool designed to improve the quality of the exchange of health information between health care professionals and patients . This system hasbeen tested on five diseases with sort throat symptom such as mononucleosis, scarlet fever, pharyngitis or tonsillitis, common cold and virusinfection and exhibited satisfactory results.

Failure Prediction of Cross-Ply Laminated Double-Serial Mechanically Fastened Composites using Fuzzy Expert System

The scope of this study is to create a model that predicts failure loads for mechanically fastened composite plates using a fuzzy expert system. The composite material used in the study was manufactured in both a fibre reinforced manner and with glass fibres. The results of a previous experimental study for cross-ply laminated composite plates that were mechanically fastened with two serial pins or bolts were used to model and predict of failure loads. Furthermore, experimental data of a preceding study were obtained with different geometrical parameters for various applied preload moments (pinned/bolted) as 2, 3, 4 and 5 Nm. In this study, a fuzzy expert system and regression analysis methods were applied by using these geometrical parameters and pinned/bolted joint configurations. Therefore, 5 geometrical parameters and 300 test data were used. According to obtained results, it was determined that the fuzzy expert system was more appropriate than the regression analysis method for modelling and prediction. Performances of the fuzzy expert system and regression analysis method were discussed in terms of error ratios and mean absolute deviations.

Soft Set Theory Oriented Forecast Combination Method for Business Failure Prediction

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

A robust algorithm based on a failure-sensitive matrix for fault diagnosis of power systems: an application on power transformers

In this paper, a robust algorithm for fault diagnosis of power system equipment based on a failure-sensitive matrix (FSM) is presented. The FSM is a dynamic matrix structure updated by multiple measurements (online) and test results (offline) on the systems. The algorithm uses many different artificial intelligence and expert system methods for adaptively detecting the location of faults, emerging failures, and causes of failures. In this algorithm, all data obtained from the power transformer, which have various nonlinear input and output parameters, are processed using the parallel matrix structure of the FSM to reach a global solution quickly. The parameters of a power transformer are used to verify the algorithm under 4 operating conditions simulated in the MATLAB--Simulink program. The obtained results show that the algorithm is convenient for determining incipient failures of a system that consists of multiple parameters.

Expert System of Fault Diagnosis for Flight Simulator Based on Fault Tree Analysis

Aiming at the problems existing in maintenance of flight simulator, considering characteristics of expert system, the architecture and fault diagnosis methods of flight simulator, the structure and key realization technology for flight simulator fault diagnosis expert system are studied; the flight simulator fault diagnosis expert system design proposal is completed. Research on transforming from fault tree pattern to rule and diagnosis knowledge representing are emphasized, expert system knowledge base is constructed by means of frame plus production knowledge representing method, then certainty and rule based backward chaining inference engine with depth-first and heuristic search mechanism is designed, the system diagnosis flow and inferring flow are also developed in this paper. Finally the expert system is tested by a fault solving demonstration.

The advent of knowledge–aided decision–making in nuclear engineering and management

This paper presents the potential application of new methods of knowledge processing and expert systems as applied to the field of nuclear safety engineering. It is considered that the synergy of these new methods of problem solving can provide powerful and flexible new tools and an adequate modelling framework to practitioners of systems engineering and management.

The Belt Conveyor Control of Large Dip Angle by FMBTES

Based on the analysis of dynamic characteristics of the belt conveyor with the long distance and the large dip angle in coal mine, a kind fusion method of Bayes theory and expert system (FMBTES) is proposed which is control method with the change regular of the start process. First, the structure and dynamics model are established for belt conveyor, the priori distributions of the system implementation state is supposed, the conditional probability of dynamics state is made using Bayes theory, next, the change regular of the start process pull force is found, and the change regular of the dynamic resistance is found for belt conveyor,on this basis,the control rule of expert system is established. The FMBTES method is verified by data simulation of Shaanxi Province Huangling Jianzhuang coal mine, which is large dip angle section of the four sections type belt conveyor system, belt length is 1200m. The dynamic characteristic of this method is better than the traditional expert system.

Development of Duck Diseases Expert System with Applying Alliance Method at Bali Provincial Livestock Office

Farming is one of the activities that have a business opportunity. One is raising ducks. The main results can be obtained from the breeding duck is a duck meat and eggs for consumption and also means praying ceremony in Bali, as well as duck egg shells that can be used for jewelry. Since the outbreak of avian influenza began in 2008, have an impact on consumer demand of ducks decreased and consumers become more careful in choosing and consuming duck. The avian influenza virus not only spread across the country of China, Thailand and Vietnam, but also in Indonesia, Bali is no exception. This is evidenced by the discovery of cases of death due to bird flu virus in some areas in Bali, among others: the regency of Karangasem, Badung, Tabanan, Klungkung and Jembrana. From this, the Bali Provincial Livestock Office took steps to develop an expert system in the detection of diseases ducks. This expert system uses a alliance method is a combination of forward chaining, backward chaining and weighted product to search the physical symptoms and behavioral symptoms duck by the name of a known disease and to determine the percentage of disease attack level in ducks. In this study, the analytical techniques used to analyze the truth is a alliance method of duck disease expert system. Activity data collection and information to support research conducted by, among others, literature studies, interviews, and observations.

Voltage Stability Control in OLTC Operation

In modern power system the voltage/reactive power control becomes more and more important because of the growth in system demands and for many utilities, the difficulty of building new power plants. In this paper we proposed to maintain the voltage profile in power system using OLTC by fuzzy expert system method. Simulation results are found in MATLAB using real data.

The Development of Load Transfer Decision Assistant System for Regional Power Grid

According to the features of distribution network, this paper designed the implementation scheme of load transfer decision assistant system. Based on the load transfer path search method and expert system method to analysis the load transfer path, the economic index and safety index evaluate function was established by the switching times , the grid loss, impulse current, load rejection and off-limit value. Through the economic security indicators, the feasibility and risk of load transfer scheme was determined.